It is important for companies to manage their revenues and -reduce their costs efficiently. These goals can be achieved through effective pricing and inventory control strategies. This thesis studies a joint multi-period ...

Stochastic programming models are large-scale optimization problems that are used to facilitate decision-making under uncertainty. Optimization algorithms for such problems need to evaluate the expected future costs of ...

In this thesis, we summarize our work on applications and methods for computational protein design. First, we apply computational protein design to address the problem of degradation in stored proteins. Specifically, we ...

The semiconductor industry is an exciting and challenging industry. Strong demand at the application end, plus the high capital intensity and rapid technological innovation in manufacturing, makes it difficult to manage ...

Uncertainty in travel time is one of the key factors that could allow us to understand and manage congestion in transportation networks. Models that incorporate uncertainty in travel time need to specify two mechanisms: ...

The purpose of this project is to incorporate a Poisson disease model into the Spatiotemporal Epidemiological Modeler (STEM) and visualize the disease spread on Google Earth. It is done through developing a Poisson disease ...

In many settings, distributed sensors provide dynamic measurements over a specified time horizon that can be used to reconstruct information such as parameters, states or initial conditions. This estimation task can be ...

This thesis investigates the impact of uncertainty on the reduction and simplification of chemical kinetics mechanisms. Chemical kinetics simulations of complex fuels are very computationally expensive, especially when ...

In this thesis, we designed and implemented a crowdsourcing system to annotate mouse behaviors in videos; this involves the development of a novel clip-based video labeling tools, that is more efficient than traditional ...

Developing parallel numerical applications, such as simulators and solvers, involves a variety of challenges in dealing with data partitioning, workload balancing, data dependencies, and synchronization. Many numerical ...

This thesis proposes new methods to solve three problems: 1) how to model and solve decision-making problems, 2) how to translate between a graphical representation of systems and a matrix representation of systems, and ...

The cryosphere is comprised of about 33 million km³ of ice, which corresponds to 70 meters of global mean sea level equivalent [30]. Simulating continental ice masses, such as the Antarctic or Greenland Ice Sheets, requires ...

This thesis aims to study the network of a nationwide distributor of a commodity product. As we cannot disclose the actual product for competitive reasons, we will present the research in terms of a similar, representative ...

The pricing problem in a multi-period setting is a challenging problem and has attracted much attention in recent years. In this thesis, we consider a monopoly and an oligopoly pricing problem. In the latter, several sellers ...

In this thesis, we utilize probabilistic reasoning and simulation methods to determine the optimal selection rule for the secretary problem with switch costs, in which a known number of applicants appear sequentially in a ...

Dynamic Time and Space Warping (DTSW) is a technique used in video matching applications to find the optimal alignment between two videos. Because DTSW requires O(N4) time and space complexity, it is only suitable for short ...

The Bayesian approach to inference problems provides a systematic way of updating prior knowledge with data. A likelihood function involving a forward model of the problem is used to incorporate data into a posterior ...